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Over the years, I have continuously attempted to formulate the traits of successful operations analysts after working with dozens of people across multiple organizations. As someone who is continuously screening, hiring, and training people on this side of the business, I have found there are five areas that a strong operations analyst should be wildly proficient; and, if he/she isnt, it is time to cut ties because he/she is most likely doing more harm than good in your organization.

Understand the Organization

Todays advanced operations are complex. They often tie together multiple software systems in conjunction with large people-based operations. A strong analyst needs to understand the business operation in its entirety (I typically require the operations analyst to do a day-in-the-life of key functions) and know how systems are integrated. The proper understanding of the intersection of processes, people, and systems in your operation lead an analyst to provide better insights from the data he/she is seeing.

Things to consider while screening: Willing to get dirty Will this person be OK with doing tasks of your workforce?

Know Where to Get Reliable Data/Information

Large organizations have data in LOTS of areas. Even worse, the inputs to these systems is usually a combination of automation and human-centric factors; and, humans do weird things. They manipulate software systems to fit the operation without telling anyone. They input data in inconsistent ways. Its a fools errand to try and normalize/control these human behaviors in large organizations. Human inputs will inadvertently change data structures and render an analyst useless unless he/she knows the shortfalls.

To find data-driven insights about your organization, an operations analyst needs to know the complete data structure, availability, and shortfalls in quality data at the company. He/she should know what systems are being used (from payroll to scheduling to customer support to native applications), what reporting features are available, and where the shortfalls in these systems exist that could muck up reports and conclusions. Often times, the software systems that are used across an operation are subject to human influence and adjustment in uncontrolled ways.

Also, SQL knowledge is a must. Any operations analyst worth his/her weight needs to be proficient in SQL. Almost all of an organizations structured (and sometimes unstructured data) can be accessed with this skillset. SQL proficiency is the new Excel.

Things to consider while screening: Ability to talk to others Will this person be comfortable talking to groups and asking about systems they use? Initiative Will this person reach out to your software providers or engineering team to find out what can and cannot be provided in terms of reporting? SQL ability What database structures has this individual worked with? What challenges has he/she overcome in structured/unstructured datasets, as well as unavailable data?

How to Manipulate Large Datasets

After tapping the highest fidelity data sources, an operations analyst is often left with joining and combining large data sets in order to start providing insights. If he/she isnt proficient in tools like SQL and/or Excel, the manipulation of this data will be overly time consuming and your pace of progress will be painstakingly slow. In the organizations I have hired for, we always test for high proficiency levels in these manipulation programs.

Things to consider while screening: Proficiency with tools What are the more complex data manipulation techniques he/she has used? I look for complex SQL query ability and command of Excel capabilities like macros and functions such as match, index, and offset (vlookup is entry-level stuff).

Valuable Insights

This is what you pay for tell me insightful things from analysis. However, this wont happen if an analyst isnt naturally curious about the business. Otherwise, you will be directly managing every task that the analyst is doing for the rest of your career. After correctly sourcing and identifying data, an analyst should be curious about how to slice and dice the data in order to provide valuable insights back to you and the organization.

Additionally, if you havent screened for someone that can meet the requirements for the first three items, he/she will draw wrong conclusions from the data which can lead to pointless projects and expensive oversights.

Things to consider while screening: Natural Curiosity Does this person constantly ask questions about the operation and how to measure it? Do they find holes in key metrics being used?

Communicate Insights to the Organization

This last pillar is often overlooked. Often times, analysts are screened for their ability to do the first four pillars, but no attention is paid to their communication/presentation abilities. Analysts should be some of the strongest teachers in an organization. Similar to the ability of explain it to me like I was in kindergarten, an analyst needs to clearly communicate findings with the rest organization. If he/she cant do that successfully, then the first three steps are worthless because the insights become worthless The rest of the organization cant understand what was done, and how to implement change.